In many industries, it is often desirable to extract meaningful information from a video sequence to provide an understanding of the objects that appear in the video, as well as any events occurring based upon those objects. In the military, for example, vehicles such as unmanned aerial vehicles (UAVs) or other remotely piloted vehicles, autonomous airborne vehicles or the like, may carry video cameras for repeatedly imaging a scene proximate the vehicles to perform intelligence and surveillance activities. In this regard, imaging such a scene permits an operator to view the scene (e.g., terrain, etc.), any objects within the scene (e.g., vehicles, people, roads, buildings, etc.), and any activities of those objects (e.g., blocking a road, crossing a bridge, loading cargo, etc.). Conventionally, an operator is required to view the video from the vehicle to provide the understanding of what is present and what is happening in the scene. That understanding, then, can be forwarded to others to thereby provide those interested with awareness of the situation in the scene.
As will be appreciated, then, increasing use of vehicles for surveillance may conventionally require larger numbers of operators. Additionally, during periods of high video activity, an operator can become overloaded, and not be able to track all of the activity that might be of importance. An automated system for processing video to extract the intelligence information can reduce the load on the operators, potentially allowing a single operator to handle multiple vehicles.
One particularly interesting application of vehicle surveillance with an automated situation and event recognition capability is convoy surveillance. In such an application, a small vehicle, such as a ScanEagle UAV, can be directed to fly cover surveillance for a convoy. Elements of the convoy, as well as any other vehicles proximate the convoy, can then be detected and tracked. In addition, the planned convoy route can be searched ahead of the convoy to look for threats. An assessment of the threat to the convoy can then be made and provided to the convoy commander. This assessment can be based on the location, and activities of other vehicles in the vicinity of the convoy, and the presence or absence of obstacles or unusual activity along the planned convoy route. Automated event processing can provide the input to the threat assessment process.
Systems and methods have been developed for video processing, such as in the context of automated video surveillance to assist an operator in analyzing and processing surveillance video. As will be appreciated, however, it is generally desirable to improve upon existing systems and methods, including those for video processing.